Measurement devices are used in nearly all branches of industry for measuring quantities, in particular physical quantities related to ongoing production processes. Measurement results indicating the measured value of the quantity are for example commonly used in process automation for monitoring, controlling and/or regulating an industrial process, in particular a production process. Thus measurement devices play a vital part in industrial processes, and a defect of a device may have severe consequences.
Industrial production sites are quite often very complex sites including a large number of measurement devices on various measurement sites. In order to ensure and/or improve quality and safety of the industrial process it is advantageous, to perform a criticality analysis preferably for every measurement device on the site. Today criticality of a device is typically determined based on a product of a probability of a defect of the respective device and a severity of the consequences of this defect. Criticality analysis thus allows identifying the device forming the greatest risk in terms of probability and severity of the consequences to the overall performance of the process.
In order to ensure, that measurement devices fulfill certain measurement properties specified for them, in particular a specified measurement accuracy, and/or comply to certain standards, they are subject to regular maintenance and calibration.
Calibration is commonly used to check conformity of a device to a given specification. During calibration the measurement device performs at least one measurement task according to a given operating procedure, during which at least one given value of the quantity to be measured by the device is provided by a corresponding reference or standard. Based on the measurement results obtained by the device with respect to the given value of the quantity to be measured, a measurement error of the device is determined. In case the measurement error exceeds a predetermined maximum permissible error, the device is considered not to conform. As a consequence, e.g. adjustment or repair of the measurement device is required, which can then be performed based on the data obtained during the calibration procedure. This includes for example adjustments of offset, gain and/or span of the measurement indication. If the measurement errors do not exceed the maximum permissible error conformity of the device is declared and generally no additional actions are performed.
Calibrations are often performed periodically after fixed calibration time intervals recommended by the manufacturer of the device, which are set solely based on technical properties of the device. Thus they are identical for all devices of the same type. For safety reasons, the calibration time intervals are typically set so short, that statistically most devices, e.g. above 90%, are still in full compliance at the end of their calibration time interval. Thus for the majority of devices it would be safely possible to apply much longer calibration time intervals. Short calibration time intervals raise the costs involved in operating these devices. This is especially relevant in applications, where a whole section of a production site has to be shut down, in order to move the device from the measurement site to the calibration site.
Basically the same considerations apply with respect to the determination of maintenance intervals.
Thus there is a need in industry to optimize calibration or maintenance intervals. Methods to determine calibration time intervals are for example described in ‘Establishment and adjustment of calibration intervals—Recommended Practice (RP-1), NCSLI, 2010, ISBN 1-58464-062-6. One method described therein is based on a reliability function giving a reliability of the type of measurement device under consideration as a function of a calibration time interval. Reliability denominates the rate of compliance, given by the percentage of devices found to be in compliance after the respective calibration time interval.
Determination of the reliability function however, requires a large amount of so called historical data. To this extent statistically relevant numbers of measurement devices of the respective type have to be calibrated after calibration time intervals covering a sufficiently large range of calibration time intervals in order to reliably determine the rate of devices which are found to be compliant after the respective calibration time intervals.
Once the reliability function is determined for the type of measurement device with a sufficient accuracy, the next calibration time interval of a specific device can be determined based on a desired reliability target to be met by the device. The reliability target denominates the probability that the device will still be compliant at the end of the calibration time interval. FIG. 1 shows an example of a reliability function RF(to) giving the percentage of devices of a certain type found in compliance as a function of the calibration time interval after which they were calibrated. If for example for a specific device a reliability target RT of 95% is desired, this means, that a 95% probability is required for this specific device to still be compliant at the end of his calibration time interval. Thus the corresponding calibration time interval T can be derived directly from the reliability function RF(to).
This method can only be applied, when sufficient historical data is available for the type of measurement device. In many cases however this data may not be available.
Depending on the properties of the type of device, in particular the expected life time, the length of calibration time intervals, and the amount of time, effort and costs involved in calibrating devices of this type, collection of the required data can be very time and cost intensive. One example are flow meters measuring a flow of a product e.g. through a pipe. Calibration of these flow meters generally requires the use of specially designed calibration rigs, capable of providing a predetermined flow of a given size with a high accuracy, which is then measured by the flow meter. These calibrations are time and cost intensive, since they usually require an interruption of the ongoing production process at the measurement site where the flow meter is operated. Also calibration time intervals especially for flow meters measuring very large flows, can be several years. Thus collection of the required data has to be performed over years.
But there can also be various other reasons, why the necessary data may not be available. One reason is e.g. that potentially available data cannot be trusted. Another reason is that resources to evaluate potentially available data cannot be provided. Also data could not be available, because the device under consideration is a newly developed device, for which no historical data has been recorded yet.